Satyen Kale

Google Research

Bio

I am a research scientist at Google Research working in the New York office. My current research is the design of efficient and practical algorithms for fundamental problems in Machine Learning and Optimization. More specifically, I am interested in decision making under uncertainty, statistical learning theory, combinatorial optimization, and convex optimization techniques such as linear and semidefinite programming.

Contact

Google
111 8th Avenue, 4th Floor
New York, NY 10011

satyen [at] satyenkale [dot] com

News

2019

ALT 2019 program chair

Aurélien Garivier and I will be program chairs for Algorithmic Learning Theory (ALT) 2019.

2018

COLT 2018 best student paper award

Dylan Foster, Haipeng Luo, Mehryar Mohri, Karthik Sridharan and I won a best student paper award at COLT 2018 for our paper Logistic Regression: The Importance of Being Improper.

2018

NIPS 2018 senior area chair

I will be serving as a senior area chair for NIPS 2018.

2018

ICLR 2018 best paper award

Sashank Reddi, Sanjiv Kumar, and I won a best paper award at ICLR 2018 for our paper On the convergence of Adam and beyond.

2017

COLT 2017 program chair

Ohad Shamir and I are the program chairs for the Conference on Learning Theory (COLT) in 2017. This is the premier conference for the theory of machine learning.

2016

COLT 2016 local chair

Daniel Hsu and I served as local chairs for the Conference on Learning Theory, 2016, held at Columbia University in New York City.

2016

ICML 2016 area chair

I was an area chair for the International Conference of Machine Learning, 2016.

2015

ICML 2015 best paper award

My paper with Alina Beygelzimer and Haipeng Luo titled Online Gradient Boosting won a best paper award at the International Conference of Machine Learning, 2015.